{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "yolov5_license_plate_train.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyO0DRC+FWVOOq7xzVWgu23p",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/sid0312/anpr_yolov5/blob/master/yolov5_license_plate_train.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bsX85iqIWJMU",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 134
        },
        "outputId": "d42c5b23-9baa-4a02-bde1-d4954f424880"
      },
      "source": [
        "!git clone https://github.com/sid0312/anpr_yolov5"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'anpr_yolov5'...\n",
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            "remote: Compressing objects: 100% (527/527), done.\u001b[K\n",
            "remote: Total 546 (delta 23), reused 516 (delta 8), pack-reused 0\u001b[K\n",
            "Receiving objects: 100% (546/546), 12.74 MiB | 28.05 MiB/s, done.\n",
            "Resolving deltas: 100% (23/23), done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DebfkL4XWOPl",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 33
        },
        "outputId": "ce3950e8-5637-434a-c60b-58f2fc21dc0a"
      },
      "source": [
        "%cd anpr_yolov5/"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/anpr_yolov5\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "u_V-6xUqWek-",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "01296dd4-4929-404b-b0da-b12cba95c414"
      },
      "source": [
        "!pip install -U -r requirements.txt"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting numpy==1.17\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/19/b9/bda9781f0a74b90ebd2e046fde1196182900bd4a8e1ea503d3ffebc50e7c/numpy-1.17.0-cp36-cp36m-manylinux1_x86_64.whl (20.4MB)\n",
            "\u001b[K     |████████████████████████████████| 20.4MB 1.8MB/s \n",
            "\u001b[?25hRequirement already up-to-date: scipy==1.4.1 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 3)) (1.4.1)\n",
            "Collecting opencv-python\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/72/c2/e9cf54ae5b1102020ef895866a67cb2e1aef72f16dd1fde5b5fb1495ad9c/opencv_python-4.2.0.34-cp36-cp36m-manylinux1_x86_64.whl (28.2MB)\n",
            "\u001b[K     |████████████████████████████████| 28.2MB 102kB/s \n",
            "\u001b[?25hCollecting matplotlib\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/e3/a8/bfd8e9ddac55a4a80235f7ccc286e4a08c97e6c4f035f21a27bcab7a51c8/matplotlib-3.2.2-cp36-cp36m-manylinux1_x86_64.whl (12.4MB)\n",
            "\u001b[K     |████████████████████████████████| 12.4MB 241kB/s \n",
            "\u001b[?25hCollecting pycocotools\n",
            "  Downloading https://files.pythonhosted.org/packages/5c/82/bcaf4d21d7027fe5165b88e3aef1910a36ed02c3e99d3385d1322ea0ba29/pycocotools-2.0.1.tar.gz\n",
            "Collecting tqdm\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/f3/76/4697ce203a3d42b2ead61127b35e5fcc26bba9a35c03b32a2bd342a4c869/tqdm-4.46.1-py2.py3-none-any.whl (63kB)\n",
            "\u001b[K     |████████████████████████████████| 71kB 7.0MB/s \n",
            "\u001b[?25hCollecting pillow\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/e0/50/8e78e6f62ffa50d6ca95c281d5a2819bef66d023ac1b723e253de5bda9c5/Pillow-7.1.2-cp36-cp36m-manylinux1_x86_64.whl (2.1MB)\n",
            "\u001b[K     |████████████████████████████████| 2.1MB 34.4MB/s \n",
            "\u001b[?25hRequirement already up-to-date: tensorboard in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 11)) (2.2.2)\n",
            "Collecting pyyaml\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/64/c2/b80047c7ac2478f9501676c988a5411ed5572f35d1beff9cae07d321512c/PyYAML-5.3.1.tar.gz (269kB)\n",
            "\u001b[K     |████████████████████████████████| 276kB 36.8MB/s \n",
            "\u001b[?25hRequirement already satisfied, skipping upgrade: python-dateutil>=2.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib->-r requirements.txt (line 7)) (2.8.1)\n",
            "Requirement already satisfied, skipping upgrade: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib->-r requirements.txt (line 7)) (2.4.7)\n",
            "Requirement already satisfied, skipping upgrade: cycler>=0.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib->-r requirements.txt (line 7)) (0.10.0)\n",
            "Requirement already satisfied, skipping upgrade: kiwisolver>=1.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib->-r requirements.txt (line 7)) (1.2.0)\n",
            "Requirement already satisfied, skipping upgrade: setuptools>=18.0 in /usr/local/lib/python3.6/dist-packages (from pycocotools->-r requirements.txt (line 8)) (47.3.1)\n",
            "Requirement already satisfied, skipping upgrade: cython>=0.27.3 in /usr/local/lib/python3.6/dist-packages (from pycocotools->-r requirements.txt (line 8)) (0.29.20)\n",
            "Requirement already satisfied, skipping upgrade: markdown>=2.6.8 in /usr/local/lib/python3.6/dist-packages (from tensorboard->-r requirements.txt (line 11)) (3.2.2)\n",
            "Requirement already satisfied, skipping upgrade: google-auth-oauthlib<0.5,>=0.4.1 in /usr/local/lib/python3.6/dist-packages (from tensorboard->-r requirements.txt (line 11)) (0.4.1)\n",
            "Requirement already satisfied, skipping upgrade: grpcio>=1.24.3 in /usr/local/lib/python3.6/dist-packages (from tensorboard->-r requirements.txt (line 11)) (1.29.0)\n",
            "Requirement already satisfied, skipping upgrade: tensorboard-plugin-wit>=1.6.0 in /usr/local/lib/python3.6/dist-packages (from tensorboard->-r requirements.txt (line 11)) (1.6.0.post3)\n",
            "Requirement already satisfied, skipping upgrade: requests<3,>=2.21.0 in /usr/local/lib/python3.6/dist-packages (from tensorboard->-r requirements.txt (line 11)) (2.23.0)\n",
            "Requirement already satisfied, skipping upgrade: wheel>=0.26; python_version >= \"3\" in /usr/local/lib/python3.6/dist-packages (from tensorboard->-r requirements.txt (line 11)) (0.34.2)\n",
            "Requirement already satisfied, skipping upgrade: six>=1.10.0 in /usr/local/lib/python3.6/dist-packages (from tensorboard->-r requirements.txt (line 11)) (1.12.0)\n",
            "Requirement already satisfied, skipping upgrade: protobuf>=3.6.0 in /usr/local/lib/python3.6/dist-packages (from tensorboard->-r requirements.txt (line 11)) (3.10.0)\n",
            "Requirement already satisfied, skipping upgrade: werkzeug>=0.11.15 in /usr/local/lib/python3.6/dist-packages (from tensorboard->-r requirements.txt (line 11)) (1.0.1)\n",
            "Requirement already satisfied, skipping upgrade: google-auth<2,>=1.6.3 in /usr/local/lib/python3.6/dist-packages (from tensorboard->-r requirements.txt (line 11)) (1.17.2)\n",
            "Requirement already satisfied, skipping upgrade: absl-py>=0.4 in /usr/local/lib/python3.6/dist-packages (from tensorboard->-r requirements.txt (line 11)) (0.9.0)\n",
            "Requirement already satisfied, skipping upgrade: importlib-metadata; python_version < \"3.8\" in /usr/local/lib/python3.6/dist-packages (from markdown>=2.6.8->tensorboard->-r requirements.txt (line 11)) (1.6.1)\n",
            "Requirement already satisfied, skipping upgrade: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.6/dist-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard->-r requirements.txt (line 11)) (1.3.0)\n",
            "Requirement already satisfied, skipping upgrade: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests<3,>=2.21.0->tensorboard->-r requirements.txt (line 11)) (1.24.3)\n",
            "Requirement already satisfied, skipping upgrade: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests<3,>=2.21.0->tensorboard->-r requirements.txt (line 11)) (2.9)\n",
            "Requirement already satisfied, skipping upgrade: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests<3,>=2.21.0->tensorboard->-r requirements.txt (line 11)) (2020.4.5.2)\n",
            "Requirement already satisfied, skipping upgrade: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests<3,>=2.21.0->tensorboard->-r requirements.txt (line 11)) (3.0.4)\n",
            "Requirement already satisfied, skipping upgrade: cachetools<5.0,>=2.0.0 in /usr/local/lib/python3.6/dist-packages (from google-auth<2,>=1.6.3->tensorboard->-r requirements.txt (line 11)) (4.1.0)\n",
            "Requirement already satisfied, skipping upgrade: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.6/dist-packages (from google-auth<2,>=1.6.3->tensorboard->-r requirements.txt (line 11)) (0.2.8)\n",
            "Requirement already satisfied, skipping upgrade: rsa<5,>=3.1.4; python_version >= \"3\" in /usr/local/lib/python3.6/dist-packages (from google-auth<2,>=1.6.3->tensorboard->-r requirements.txt (line 11)) (4.6)\n",
            "Requirement already satisfied, skipping upgrade: zipp>=0.5 in /usr/local/lib/python3.6/dist-packages (from importlib-metadata; python_version < \"3.8\"->markdown>=2.6.8->tensorboard->-r requirements.txt (line 11)) (3.1.0)\n",
            "Requirement already satisfied, skipping upgrade: oauthlib>=3.0.0 in /usr/local/lib/python3.6/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard->-r requirements.txt (line 11)) (3.1.0)\n",
            "Requirement already satisfied, skipping upgrade: pyasn1<0.5.0,>=0.4.6 in /usr/local/lib/python3.6/dist-packages (from pyasn1-modules>=0.2.1->google-auth<2,>=1.6.3->tensorboard->-r requirements.txt (line 11)) (0.4.8)\n",
            "Building wheels for collected packages: pycocotools, pyyaml\n",
            "  Building wheel for pycocotools (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pycocotools: filename=pycocotools-2.0.1-cp36-cp36m-linux_x86_64.whl size=267029 sha256=c384a16e422ad600d51979d03c3f3624798013abcce57e5ce2e34fbfef0f1e51\n",
            "  Stored in directory: /root/.cache/pip/wheels/86/19/08/49b25f258ead1f861c9ab2fc41f73636f2928859adbb0e9797\n",
            "  Building wheel for pyyaml (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pyyaml: filename=PyYAML-5.3.1-cp36-cp36m-linux_x86_64.whl size=44621 sha256=7d6c1f3889a3a0e95706054c64aab1d24c98b669338377555693704014a7765b\n",
            "  Stored in directory: /root/.cache/pip/wheels/a7/c1/ea/cf5bd31012e735dc1dfea3131a2d5eae7978b251083d6247bd\n",
            "Successfully built pycocotools pyyaml\n",
            "\u001b[31mERROR: datascience 0.10.6 has requirement folium==0.2.1, but you'll have folium 0.8.3 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: albumentations 0.1.12 has requirement imgaug<0.2.7,>=0.2.5, but you'll have imgaug 0.2.9 which is incompatible.\u001b[0m\n",
            "Installing collected packages: numpy, opencv-python, matplotlib, pycocotools, tqdm, pillow, pyyaml\n",
            "  Found existing installation: numpy 1.18.5\n",
            "    Uninstalling numpy-1.18.5:\n",
            "      Successfully uninstalled numpy-1.18.5\n",
            "  Found existing installation: opencv-python 4.1.2.30\n",
            "    Uninstalling opencv-python-4.1.2.30:\n",
            "      Successfully uninstalled opencv-python-4.1.2.30\n",
            "  Found existing installation: matplotlib 3.2.1\n",
            "    Uninstalling matplotlib-3.2.1:\n",
            "      Successfully uninstalled matplotlib-3.2.1\n",
            "  Found existing installation: pycocotools 2.0.0\n",
            "    Uninstalling pycocotools-2.0.0:\n",
            "      Successfully uninstalled pycocotools-2.0.0\n",
            "  Found existing installation: tqdm 4.41.1\n",
            "    Uninstalling tqdm-4.41.1:\n",
            "      Successfully uninstalled tqdm-4.41.1\n",
            "  Found existing installation: Pillow 7.0.0\n",
            "    Uninstalling Pillow-7.0.0:\n",
            "      Successfully uninstalled Pillow-7.0.0\n",
            "  Found existing installation: PyYAML 3.13\n",
            "    Uninstalling PyYAML-3.13:\n",
            "      Successfully uninstalled PyYAML-3.13\n",
            "Successfully installed matplotlib-3.2.2 numpy-1.17.0 opencv-python-4.2.0.34 pillow-7.1.2 pycocotools-2.0.1 pyyaml-5.3.1 tqdm-4.46.1\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "PIL",
                  "matplotlib",
                  "mpl_toolkits",
                  "numpy",
                  "tqdm"
                ]
              }
            }
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "By9_ecFJWhhr",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 33
        },
        "outputId": "af004b19-c4ec-461d-a431-df1295404a43"
      },
      "source": [
        "!pwd"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Lbddvo8qYE2X",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 33
        },
        "outputId": "f054c228-2d3e-4972-fe7d-e375df9a3f1d"
      },
      "source": [
        "%cd anpr_yolov5/"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/anpr_yolov5\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Y8NzltpQYIAd",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "47d00019-fd65-442e-ceab-afbcf9c0e4ce"
      },
      "source": [
        "!python train.py --img 640 --batch 8 --epochs 100 --data ./data/license_plate.yaml --cfg ./models/yolov5s.yaml --weights '' --device 0"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Apex recommended for faster mixed precision training: https://github.com/NVIDIA/apex\n",
            "{'lr0': 0.01, 'momentum': 0.937, 'weight_decay': 0.0005, 'giou': 0.05, 'cls': 0.58, 'cls_pw': 1.0, 'obj': 1.0, 'obj_pw': 1.0, 'iou_t': 0.2, 'anchor_t': 4.0, 'fl_gamma': 0.0, 'hsv_h': 0.014, 'hsv_s': 0.68, 'hsv_v': 0.36, 'degrees': 0.0, 'translate': 0.0, 'scale': 0.5, 'shear': 0.0}\n",
            "Namespace(adam=False, batch_size=8, bucket='', cache_images=False, cfg='./models/yolov5s.yaml', data='./data/license_plate.yaml', device='0', epochs=100, evolve=False, img_size=[640], multi_scale=False, name='', noautoanchor=False, nosave=False, notest=False, rect=False, resume=False, single_cls=False, weights='')\n",
            "Using CUDA device0 _CudaDeviceProperties(name='Tesla K80', total_memory=11441MB)\n",
            "\n",
            "2020-06-20 15:42:17.734961: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1\n",
            "Start Tensorboard with \"tensorboard --logdir=runs\", view at http://localhost:6006/\n",
            "\n",
            "              from  n    params  module                                  arguments                     \n",
            "  0             -1  1      3520  models.common.Focus                     [3, 32, 3]                    \n",
            "  1             -1  1     18560  models.common.Conv                      [32, 64, 3, 2]                \n",
            "  2             -1  1     20672  models.common.Bottleneck                [64, 64]                      \n",
            "  3             -1  1     73984  models.common.Conv                      [64, 128, 3, 2]               \n",
            "  4             -1  1    161152  models.common.BottleneckCSP             [128, 128, 3]                 \n",
            "  5             -1  1    295424  models.common.Conv                      [128, 256, 3, 2]              \n",
            "  6             -1  1    641792  models.common.BottleneckCSP             [256, 256, 3]                 \n",
            "  7             -1  1   1180672  models.common.Conv                      [256, 512, 3, 2]              \n",
            "  8             -1  1    656896  models.common.SPP                       [512, 512, [5, 9, 13]]        \n",
            "  9             -1  1   1905152  models.common.BottleneckCSP             [512, 512, 2]                 \n",
            " 10             -1  1   1248768  models.common.BottleneckCSP             [512, 512, 1, False]          \n",
            " 11             -1  1      9234  torch.nn.modules.conv.Conv2d            [512, 18, 1, 1]               \n",
            " 12             -2  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          \n",
            " 13        [-1, 6]  1         0  models.common.Concat                    [1]                           \n",
            " 14             -1  1    197120  models.common.Conv                      [768, 256, 1, 1]              \n",
            " 15             -1  1    313088  models.common.BottleneckCSP             [256, 256, 1, False]          \n",
            " 16             -1  1      4626  torch.nn.modules.conv.Conv2d            [256, 18, 1, 1]               \n",
            " 17             -2  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          \n",
            " 18        [-1, 4]  1         0  models.common.Concat                    [1]                           \n",
            " 19             -1  1     49408  models.common.Conv                      [384, 128, 1, 1]              \n",
            " 20             -1  1     78720  models.common.BottleneckCSP             [128, 128, 1, False]          \n",
            " 21             -1  1      2322  torch.nn.modules.conv.Conv2d            [128, 18, 1, 1]               \n",
            " 22   [-1, 16, 11]  1         0  models.yolo.Detect                      [1, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]]]\n",
            "Model Summary: 165 layers, 6.86111e+06 parameters, 6.86111e+06 gradients\n",
            "\n",
            "Optimizer groups: 54 .bias, 60 conv.weight, 51 other\n",
            "Reading image shapes: 100% 201/201 [00:00<00:00, 7678.80it/s]\n",
            "Caching labels /content/anpr_yolov5/data/train.txt (201 found, 0 missing, 0 empty, 0 duplicate, for 201 images): 100% 201/201 [00:00<00:00, 6999.68it/s]\n",
            "Reading image shapes: 100% 36/36 [00:00<00:00, 9331.62it/s]\n",
            "Caching labels /content/anpr_yolov5/data/val.txt (36 found, 0 missing, 0 empty, 0 duplicate, for 36 images): 100% 36/36 [00:00<00:00, 6796.68it/s]\n",
            "\n",
            "Analyzing anchors... Best Possible Recall (BPR) = 1.0000\n",
            "Image sizes 640 train, 640 test\n",
            "Using 2 dataloader workers\n",
            "Starting training for 100 epochs...\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "      0/99     1.38G    0.1169   0.03331         0    0.1502         3       640: 100% 26/26 [00:27<00:00,  1.05s/it]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:19<00:00,  3.99s/it]\n",
            "                 all          36          36           0           0     0.00658    0.000891\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "      1/99     2.25G   0.09423   0.03492         0    0.1292         4       640: 100% 26/26 [00:13<00:00,  1.95it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:02<00:00,  2.31it/s]\n",
            "                 all          36          36           0           0     0.00513    0.000771\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "      2/99     2.25G    0.0909   0.03038         0    0.1213         1       640: 100% 26/26 [00:12<00:00,  2.00it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:02<00:00,  2.19it/s]\n",
            "                 all          36          36           0           0     0.00388    0.000655\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "      3/99     2.25G   0.09001   0.03173         0    0.1217         3       640: 100% 26/26 [00:13<00:00,  1.97it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.53it/s]\n",
            "                 all          36          36           0           0     0.00501    0.000755\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "      4/99     2.25G   0.08448   0.02993         0    0.1144         1       640: 100% 26/26 [00:12<00:00,  2.03it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.76it/s]\n",
            "                 all          36          36           0           0     0.00352    0.000737\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "      5/99     2.25G   0.08786   0.03158         0    0.1194         2       640: 100% 26/26 [00:12<00:00,  2.16it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.82it/s]\n",
            "                 all          36          36           0           0     0.00349    0.000548\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "      6/99     2.25G   0.08436   0.03424         0    0.1186         4       640: 100% 26/26 [00:12<00:00,  2.10it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.11it/s]\n",
            "                 all          36          36           0           0    0.000637    0.000104\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "      7/99     2.25G   0.08412   0.03038         0    0.1145         2       640: 100% 26/26 [00:11<00:00,  2.23it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.96it/s]\n",
            "                 all          36          36           0           0     0.00561    0.000743\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "      8/99     2.25G   0.08553   0.03302         0    0.1186         4       640: 100% 26/26 [00:12<00:00,  2.16it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.99it/s]\n",
            "                 all          36          36           0           0     0.00341    0.000489\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "      9/99     2.25G   0.08041   0.03374         0    0.1142         2       640: 100% 26/26 [00:11<00:00,  2.24it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.79it/s]\n",
            "                 all          36          36           0           0     0.00702     0.00103\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     10/99     2.25G    0.0805   0.03219         0    0.1127         1       640: 100% 26/26 [00:11<00:00,  2.26it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.00it/s]\n",
            "                 all          36          36           0           0     0.00273    0.000387\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     11/99     2.25G   0.08045   0.03313         0    0.1136         2       640: 100% 26/26 [00:11<00:00,  2.18it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.32it/s]\n",
            "                 all          36          36           0           0    2.57e-05    2.57e-06\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     12/99     2.25G   0.08112   0.03179         0    0.1129         2       640: 100% 26/26 [00:11<00:00,  2.26it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.01it/s]\n",
            "                 all          36          36           0           0    4.88e-05    8.39e-06\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     13/99     2.25G   0.08016   0.03227         0    0.1124         1       640: 100% 26/26 [00:11<00:00,  2.27it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.19it/s]\n",
            "                 all          36          36           0           0    0.000289     5.6e-05\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     14/99     2.25G   0.08082   0.03106         0    0.1119         2       640: 100% 26/26 [00:12<00:00,  2.16it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.05it/s]\n",
            "                 all          36          36           0           0     0.00531    0.000841\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     15/99     2.25G   0.07991   0.03201         0    0.1119         1       640: 100% 26/26 [00:11<00:00,  2.21it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.78it/s]\n",
            "                 all          36          36           0           0     0.00497     0.00131\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     16/99     2.25G   0.08351   0.03443         0    0.1179         4       640: 100% 26/26 [00:12<00:00,  2.16it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.06it/s]\n",
            "                 all          36          36           0           0     0.00852     0.00126\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     17/99     2.25G   0.08014   0.03091         0    0.1111         2       640: 100% 26/26 [00:11<00:00,  2.20it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.12it/s]\n",
            "                 all          36          36           1      0.0278      0.0402      0.0048\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     18/99     2.25G   0.08107   0.03029         0    0.1114         2       640: 100% 26/26 [00:12<00:00,  2.14it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.97it/s]\n",
            "                 all          36          36           0           0      0.0349     0.00459\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     19/99     2.25G   0.07779   0.03191         0    0.1097         1       640: 100% 26/26 [00:12<00:00,  2.15it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.98it/s]\n",
            "                 all          36          36           1      0.0278       0.045      0.0103\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     20/99     2.25G   0.08078   0.03134         0    0.1121         3       640: 100% 26/26 [00:11<00:00,  2.20it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.12it/s]\n",
            "                 all          36          36           0           0       0.046     0.00694\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     21/99     2.25G   0.07842   0.03567         0    0.1141         4       640: 100% 26/26 [00:11<00:00,  2.17it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.05it/s]\n",
            "                 all          36          36           0           0      0.0274      0.0041\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     22/99     2.25G   0.07127   0.03051         0    0.1018         0       640: 100% 26/26 [00:11<00:00,  2.24it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.07it/s]\n",
            "                 all          36          36           0           0      0.0357     0.00827\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     23/99     2.25G    0.0759   0.03397         0    0.1099         1       640: 100% 26/26 [00:12<00:00,  2.13it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.84it/s]\n",
            "                 all          36          36           0           0      0.0262      0.0047\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     24/99     2.25G   0.07445   0.03243         0    0.1069         1       640: 100% 26/26 [00:11<00:00,  2.17it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.90it/s]\n",
            "                 all          36          36           0           0      0.0645      0.0146\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     25/99     2.25G   0.07627    0.0349         0    0.1112         4       640: 100% 26/26 [00:12<00:00,  2.07it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.06it/s]\n",
            "                 all          36          36           0           0      0.0822      0.0164\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     26/99     2.25G    0.0734   0.03307         0    0.1065         2       640: 100% 26/26 [00:12<00:00,  2.15it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.05it/s]\n",
            "                 all          36          36           0           0      0.0689      0.0112\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     27/99     2.25G   0.07229     0.031         0    0.1033         1       640: 100% 26/26 [00:11<00:00,  2.29it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.06it/s]\n",
            "                 all          36          36       0.257      0.0833       0.159      0.0276\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     28/99     2.25G   0.07292   0.03391         0    0.1068         2       640: 100% 26/26 [00:12<00:00,  2.11it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.84it/s]\n",
            "                 all          36          36       0.625       0.186       0.262      0.0652\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     29/99     2.25G   0.07011   0.03135         0    0.1015         1       640: 100% 26/26 [00:12<00:00,  2.16it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.16it/s]\n",
            "                 all          36          36       0.244       0.528        0.32      0.0806\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     30/99     2.25G   0.06767   0.03266         0    0.1003         3       640: 100% 26/26 [00:12<00:00,  2.15it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.99it/s]\n",
            "                 all          36          36       0.145       0.472       0.253      0.0738\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     31/99     2.25G    0.0699   0.03105         0     0.101         4       640: 100% 26/26 [00:11<00:00,  2.21it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.92it/s]\n",
            "                 all          36          36       0.113       0.472       0.129      0.0219\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     32/99     2.25G   0.06705   0.03039         0   0.09745         1       640: 100% 26/26 [00:12<00:00,  2.14it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.97it/s]\n",
            "                 all          36          36       0.138       0.505       0.133      0.0249\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     33/99     2.25G    0.0685    0.0293         0   0.09779         2       640: 100% 26/26 [00:12<00:00,  2.15it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.80it/s]\n",
            "                 all          36          36       0.298       0.333       0.229      0.0516\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     34/99     2.25G   0.06388    0.0324         0   0.09629         2       640: 100% 26/26 [00:11<00:00,  2.26it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.98it/s]\n",
            "                 all          36          36       0.187       0.694       0.275      0.0692\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     35/99     2.25G   0.06561    0.0316         0   0.09721         4       640: 100% 26/26 [00:11<00:00,  2.24it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.13it/s]\n",
            "                 all          36          36       0.162       0.639       0.221      0.0453\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     36/99     2.25G   0.06993   0.02929         0   0.09922         2       640: 100% 26/26 [00:11<00:00,  2.22it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.07it/s]\n",
            "                 all          36          36       0.452       0.361       0.273      0.0525\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     37/99     2.25G   0.06065   0.03016         0    0.0908         1       640: 100% 26/26 [00:11<00:00,  2.19it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.01it/s]\n",
            "                 all          36          36      0.0893         0.7       0.231      0.0621\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     38/99     2.25G   0.06468   0.02967         0   0.09435         4       640: 100% 26/26 [00:11<00:00,  2.19it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.03it/s]\n",
            "                 all          36          36       0.106       0.444      0.0812      0.0149\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     39/99     2.25G   0.06308   0.02859         0   0.09168         1       640: 100% 26/26 [00:11<00:00,  2.21it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.11it/s]\n",
            "                 all          36          36       0.298       0.639       0.458       0.114\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     40/99     2.25G   0.06297   0.02963         0    0.0926         2       640: 100% 26/26 [00:11<00:00,  2.27it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.83it/s]\n",
            "                 all          36          36       0.327        0.75       0.456       0.124\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     41/99     2.25G   0.05988   0.02858         0   0.08845         1       640: 100% 26/26 [00:11<00:00,  2.23it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.17it/s]\n",
            "                 all          36          36       0.297       0.806       0.411      0.0972\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     42/99     2.25G   0.05988   0.03164         0   0.09152         3       640: 100% 26/26 [00:11<00:00,  2.24it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.31it/s]\n",
            "                 all          36          36       0.374        0.75       0.511       0.156\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     43/99     2.25G   0.05582   0.02777         0    0.0836         1       640: 100% 26/26 [00:11<00:00,  2.22it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.23it/s]\n",
            "                 all          36          36       0.257       0.722       0.522       0.149\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     44/99     2.25G   0.06075   0.02844         0    0.0892         2       640: 100% 26/26 [00:11<00:00,  2.21it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.08it/s]\n",
            "                 all          36          36      0.0137        0.75      0.0458     0.00566\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     45/99     2.25G    0.0583   0.02885         0   0.08716         2       640: 100% 26/26 [00:11<00:00,  2.17it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.17it/s]\n",
            "                 all          36          36       0.206       0.806        0.44       0.195\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     46/99     2.25G   0.05697   0.02899         0   0.08596         4       640: 100% 26/26 [00:11<00:00,  2.18it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.28it/s]\n",
            "                 all          36          36       0.207       0.861       0.599       0.174\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     47/99     2.25G   0.05671   0.02761         0   0.08433         2       640: 100% 26/26 [00:11<00:00,  2.20it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.92it/s]\n",
            "                 all          36          36       0.338       0.937       0.796       0.337\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     48/99     2.25G    0.0561    0.0263         0    0.0824         2       640: 100% 26/26 [00:11<00:00,  2.18it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  2.91it/s]\n",
            "                 all          36          36       0.111       0.556       0.272      0.0459\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     49/99     2.25G   0.05386   0.02739         0   0.08125         1       640: 100% 26/26 [00:12<00:00,  2.14it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.06it/s]\n",
            "                 all          36          36       0.207       0.694       0.423       0.095\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     50/99     2.25G    0.0547   0.02823         0   0.08293         4       640: 100% 26/26 [00:11<00:00,  2.20it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.46it/s]\n",
            "                 all          36          36       0.448       0.944       0.816       0.407\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     51/99     2.25G   0.04925   0.02594         0   0.07519         3       640: 100% 26/26 [00:11<00:00,  2.20it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.64it/s]\n",
            "                 all          36          36       0.335       0.944       0.779       0.343\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     52/99     2.25G   0.05404   0.02533         0   0.07937         3       640: 100% 26/26 [00:12<00:00,  2.15it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.39it/s]\n",
            "                 all          36          36       0.352           1       0.874       0.367\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     53/99     2.25G    0.0553   0.02444         0   0.07974         3       640: 100% 26/26 [00:11<00:00,  2.19it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.89it/s]\n",
            "                 all          36          36        0.34       0.972       0.862       0.405\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     54/99     2.25G   0.05075   0.02508         0   0.07583         3       640: 100% 26/26 [00:11<00:00,  2.21it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.76it/s]\n",
            "                 all          36          36       0.413       0.944       0.863       0.437\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     55/99     2.25G   0.05378   0.02513         0   0.07892         2       640: 100% 26/26 [00:12<00:00,  2.09it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.51it/s]\n",
            "                 all          36          36       0.336       0.889       0.808       0.304\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     56/99     2.25G    0.0481   0.02278         0   0.07088         1       640: 100% 26/26 [00:12<00:00,  2.16it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.06it/s]\n",
            "                 all          36          36       0.301       0.778       0.674       0.171\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     57/99     2.25G   0.05073   0.02332         0   0.07405         2       640: 100% 26/26 [00:11<00:00,  2.18it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.97it/s]\n",
            "                 all          36          36       0.416       0.944        0.88       0.433\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     58/99     2.25G   0.04847   0.02387         0   0.07234         1       640: 100% 26/26 [00:11<00:00,  2.19it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.59it/s]\n",
            "                 all          36          36       0.503       0.917       0.882       0.409\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     59/99     2.25G   0.05019   0.02615         0   0.07634         4       640: 100% 26/26 [00:11<00:00,  2.19it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.77it/s]\n",
            "                 all          36          36       0.439       0.972       0.928       0.452\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     60/99     2.25G   0.04729   0.02209         0   0.06939         1       640: 100% 26/26 [00:11<00:00,  2.30it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.30it/s]\n",
            "                 all          36          36       0.555       0.889       0.892       0.358\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     61/99     2.25G   0.04701   0.02446         0   0.07147         4       640: 100% 26/26 [00:11<00:00,  2.22it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.01it/s]\n",
            "                 all          36          36         0.5       0.889       0.881       0.419\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     62/99     2.25G   0.04715   0.02456         0   0.07171         3       640: 100% 26/26 [00:11<00:00,  2.22it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.70it/s]\n",
            "                 all          36          36       0.348       0.972        0.89       0.454\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     63/99     2.25G   0.04694   0.02376         0    0.0707         1       640: 100% 26/26 [00:11<00:00,  2.17it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.24it/s]\n",
            "                 all          36          36       0.437       0.917       0.908       0.383\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     64/99     2.25G   0.04681   0.02374         0   0.07054         2       640: 100% 26/26 [00:11<00:00,  2.23it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.05it/s]\n",
            "                 all          36          36       0.387       0.889       0.876       0.347\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     65/99     2.25G   0.04493   0.02428         0   0.06921         2       640: 100% 26/26 [00:11<00:00,  2.18it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.15it/s]\n",
            "                 all          36          36       0.452       0.917       0.872       0.401\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     66/99     2.25G   0.04748   0.02302         0    0.0705         1       640: 100% 26/26 [00:11<00:00,  2.23it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.51it/s]\n",
            "                 all          36          36       0.496       0.944       0.897       0.397\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     67/99     2.25G   0.04585   0.02301         0   0.06886         1       640: 100% 26/26 [00:11<00:00,  2.21it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.24it/s]\n",
            "                 all          36          36       0.547       0.917       0.901        0.36\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     68/99     2.25G   0.04291   0.02198         0   0.06489         0       640: 100% 26/26 [00:11<00:00,  2.17it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.84it/s]\n",
            "                 all          36          36       0.554       0.861       0.841       0.306\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     69/99     2.25G    0.0452   0.02292         0   0.06812         2       640: 100% 26/26 [00:11<00:00,  2.20it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  3.72it/s]\n",
            "                 all          36          36       0.552       0.972        0.95       0.458\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     70/99     2.25G   0.04539    0.0212         0    0.0666         2       640: 100% 26/26 [00:12<00:00,  2.17it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.27it/s]\n",
            "                 all          36          36       0.548           1       0.967       0.485\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     71/99     2.25G   0.04522   0.02334         0   0.06856         2       640: 100% 26/26 [00:12<00:00,  2.15it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.32it/s]\n",
            "                 all          36          36        0.47       0.944       0.888        0.42\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     72/99     2.25G   0.04342   0.02259         0   0.06601         3       640: 100% 26/26 [00:11<00:00,  2.23it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.44it/s]\n",
            "                 all          36          36       0.509       0.889       0.846       0.292\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     73/99     2.25G   0.04522    0.0228         0   0.06802         1       640: 100% 26/26 [00:11<00:00,  2.24it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.08it/s]\n",
            "                 all          36          36       0.536       0.917       0.892       0.409\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     74/99     2.25G   0.04479   0.02256         0   0.06735         1       640: 100% 26/26 [00:12<00:00,  2.15it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.35it/s]\n",
            "                 all          36          36       0.625       0.944        0.93        0.38\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     75/99     2.25G   0.04253   0.02202         0   0.06456         1       640: 100% 26/26 [00:12<00:00,  2.07it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.63it/s]\n",
            "                 all          36          36        0.64       0.972       0.966       0.463\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     76/99     2.25G    0.0428   0.02212         0   0.06492         2       640: 100% 26/26 [00:11<00:00,  2.19it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.50it/s]\n",
            "                 all          36          36       0.625       0.944       0.927        0.34\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     77/99     2.25G   0.04338    0.0202         0   0.06358         2       640: 100% 26/26 [00:12<00:00,  2.16it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.02it/s]\n",
            "                 all          36          36       0.733       0.972       0.946       0.478\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     78/99     2.25G   0.04415   0.02228         0   0.06643         3       640: 100% 26/26 [00:12<00:00,  2.11it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.67it/s]\n",
            "                 all          36          36       0.634       0.972        0.97       0.481\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     79/99     2.25G   0.04215    0.0212         0   0.06335         4       640: 100% 26/26 [00:11<00:00,  2.24it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.42it/s]\n",
            "                 all          36          36       0.551       0.944       0.952         0.4\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     80/99     2.25G   0.04128   0.02236         0   0.06363         1       640: 100% 26/26 [00:12<00:00,  2.16it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.33it/s]\n",
            "                 all          36          36       0.595       0.972       0.982       0.461\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     81/99     2.25G   0.03945   0.02197         0   0.06142         4       640: 100% 26/26 [00:11<00:00,  2.20it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.76it/s]\n",
            "                 all          36          36        0.62       0.972       0.985       0.493\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     82/99     2.25G    0.0396   0.02052         0   0.06013         1       640: 100% 26/26 [00:11<00:00,  2.22it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.75it/s]\n",
            "                 all          36          36       0.626           1       0.981       0.493\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     83/99     2.25G   0.03889   0.02068         0   0.05957         1       640: 100% 26/26 [00:12<00:00,  2.14it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.91it/s]\n",
            "                 all          36          36       0.606       0.972       0.978       0.435\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     84/99     2.25G   0.04027   0.02168         0   0.06196         3       640: 100% 26/26 [00:11<00:00,  2.25it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.61it/s]\n",
            "                 all          36          36       0.648       0.972       0.981       0.471\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     85/99     2.25G   0.03967   0.02194         0   0.06161         2       640: 100% 26/26 [00:11<00:00,  2.23it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.83it/s]\n",
            "                 all          36          36       0.662       0.972        0.98        0.46\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     86/99     2.25G   0.03909    0.0205         0    0.0596         2       640: 100% 26/26 [00:11<00:00,  2.26it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.79it/s]\n",
            "                 all          36          36       0.666       0.972       0.977       0.461\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     87/99     2.25G   0.04045   0.02048         0   0.06093         1       640: 100% 26/26 [00:11<00:00,  2.24it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.70it/s]\n",
            "                 all          36          36       0.615       0.972        0.97       0.441\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     88/99     2.25G   0.03824   0.02138         0   0.05962         0       640: 100% 26/26 [00:11<00:00,  2.28it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.83it/s]\n",
            "                 all          36          36       0.626       0.944       0.949       0.447\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     89/99     2.25G   0.04085   0.02006         0    0.0609         2       640: 100% 26/26 [00:11<00:00,  2.22it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.70it/s]\n",
            "                 all          36          36       0.541       0.972       0.978       0.513\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     90/99     2.25G   0.03993   0.01996         0   0.05989         1       640: 100% 26/26 [00:11<00:00,  2.25it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.40it/s]\n",
            "                 all          36          36        0.52       0.972       0.978       0.469\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     91/99     2.25G   0.03726   0.02084         0    0.0581         2       640: 100% 26/26 [00:12<00:00,  2.16it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.40it/s]\n",
            "                 all          36          36       0.542       0.972       0.976       0.474\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     92/99     2.25G   0.03851   0.02138         0   0.05989         2       640: 100% 26/26 [00:11<00:00,  2.23it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.65it/s]\n",
            "                 all          36          36       0.628       0.972       0.974       0.465\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     93/99     2.25G   0.03882   0.02117         0   0.05999         2       640: 100% 26/26 [00:12<00:00,  2.16it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.77it/s]\n",
            "                 all          36          36       0.652       0.972       0.981       0.483\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     94/99     2.25G   0.03889   0.02179         0   0.06068         2       640: 100% 26/26 [00:12<00:00,  2.15it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.65it/s]\n",
            "                 all          36          36       0.622       0.972       0.976       0.428\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     95/99     2.25G   0.03688   0.02147         0   0.05835         2       640: 100% 26/26 [00:11<00:00,  2.18it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.54it/s]\n",
            "                 all          36          36       0.657       0.972       0.975       0.476\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     96/99     2.25G    0.0366   0.02077         0   0.05738         1       640: 100% 26/26 [00:11<00:00,  2.17it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.64it/s]\n",
            "                 all          36          36       0.604       0.972       0.969       0.352\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     97/99     2.25G   0.03849   0.02001         0    0.0585         1       640: 100% 26/26 [00:11<00:00,  2.20it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.41it/s]\n",
            "                 all          36          36       0.532       0.972       0.957        0.42\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     98/99     2.25G   0.03667   0.02162         0   0.05829         4       640: 100% 26/26 [00:11<00:00,  2.21it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.89it/s]\n",
            "                 all          36          36       0.563       0.972       0.977       0.407\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     99/99     2.25G   0.03932   0.02027         0   0.05959         1       640: 100% 26/26 [00:11<00:00,  2.18it/s]\n",
            "               Class      Images     Targets           P           R      mAP@.5  mAP@.5:.95: 100% 5/5 [00:01<00:00,  4.95it/s]\n",
            "                 all          36          36       0.659       0.972       0.978       0.471\n",
            "100 epochs completed in 0.387 hours.\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PL5A90EGfKVX",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}